Category: Artificial Intelligence

Emerging sustainability reporting requirements demand standardized, auditable processes with flexibility to adapt to evolving frameworks. For many organizations, the challenge isn’t data availability, it’s synthesizing fragmented information into coherent, audit-ready disclosures. Sustainability data resides across facility management systems, procurement platforms, HR tools, carbon accounting solutions, and operational databases. Many traditional business intelligence tools are not […]

This is part 3 of our three-part series on how Amazon Web Services (AWS) aligns with MPA Content Security Best Practices with a particular focus on media archives.

This guide walks one agent through all six pillars: a Parts Inventory Agent for an automotive manufacturing plant.

In this post, we demonstrate how a large North American Utility is currently running a multi-agent AI architecture on Amazon Bedrock AgentCore to compress alarm triage from hours to minutes, avoiding the manual, multi-system investigation that operators perform dozens of times per shift. We will walk through the industry problem, the multi-agent design, and a reference implementation on GitHub that you can deploy into your own environment.

As part of its ongoing commitment to operational excellence, Mary Kay sought to further accelerate the investigation and resolution of routine infrastructure events through AI-powered automation and intelligent orchestration by activating a capability most Amazon Web Services (AWS) Enterprise Support customers already pay for but never use: the AWS DevOps Agent.

In this post, we show how you can use AWS HealthLake to meet CMS-0057-F requirements while building a FHIR data solution that accelerates your broader digital transformation.

We are excited to announce resource matching for AWS HealthLake, now available in gated preview. Resource matching is a built-in capability that automatically identifies FHIR resources representing the same real-world entity and links them without modifying or merging the original data.

This blog post introduces a serverless dynamic pricing platform built on Amazon Web Services (AWS) that helps restaurants automatically adjust menu prices based on real-time demand patterns. The solution enables restaurants to maximize revenue during peak hours while attracting price-sensitive customers during slower periods.

Across R&D organizations, AI agents are beginning to design molecules, plan syntheses, execute assays, and analyze experimental data. But these systems often operate without awareness of prior experiments, failed approaches, or parallel work happening across the organization. In this blog, learn how Sanofi recognized this limitation early and partnered with Amazon Web Services (AWS) to reimagine the foundation for AI-enabled discovery.

In the retail and consumer packaged goods (CPG) industry, accurate food labeling is a critical safety requirement. Retailers face an increasingly complex challenge: manually verifying that thousands of packaged foods comply with FDA regulations—particularly the allergen labeling requirements under the Food Allergen Labeling and Consumer Protection Act (FALCPA) of 2004.